Top Artificial Intelligence Jobs

Lead the architecture, strategy, and development of enterprise generative AI initiatives. Define AI/ML standards, guide scalable model deployment, conduct advanced research, and collaborate with executives, product, data science, and engineering teams. Mentor technical leaders, promote MLOps and responsible AI practices, optimize models for cost and performance, and represent the organization through publications and industry engagement.

Build and scale production-grade agentic AI systems using Google ADK and related platforms. Lead technical strategy, architecture, integrations, testing, deployment, monitoring, and lifecycle management for multi-agent workflows. Integrate agents with enterprise systems through APIs and MCP, establish observability and quality practices, lead complex cross-functional projects, and mentor engineers on agent development, safety, and operational excellence.

Lead UKG’s AI FinOps function by building cost models, token attribution, forecasts, unit economics, governance, and executive reporting across AI workloads and cloud providers. Partner with Engineering, Product, Finance, Procurement, and Cloud Operations to optimize model selection, infrastructure, capacity, commitments, and margins. Establish guardrails, self-service tools, dashboards, and operating rhythms that connect AI consumption to adoption, customer value, savings, and investment decisions.

Design, build, deploy, and maintain production-grade agentic AI systems using Google ADK and related platforms. Lead technical strategy and complex agent projects, architect multi-agent workflows, integrate enterprise tools and APIs, and ensure service reliability through testing, observability, telemetry, and lifecycle management. Mentor engineers, influence technical decisions, and drive innovation in agent development, orchestration, safety, and performance optimization.

Define enterprise-wide agentic AI strategy and architecture using Google ADK and related platforms. Build multi-agent systems, governance frameworks, integrations, safety guardrails, monitoring, and operational standards. Influence technical direction across organizations, mentor senior engineering talent, lead complex initiatives, evaluate emerging AI technologies, and represent UKG through partnerships, publications, and industry engagement.

Build, deploy, and maintain production-grade agentic AI systems using Google ADK and related platforms. Develop agent workflows, tools, integrations, orchestration patterns, testing frameworks, observability, and lifecycle operations. Collaborate with product and engineering teams, contribute to architecture and design decisions, review code, troubleshoot service health, document solutions, and mentor engineers. Apply DevOps practices and evaluate emerging agentic AI technologies to improve enterprise workforce platform capabilities.

Develops secure, scalable software solutions for JPMorganChase’s CX Loyalty Travel team. Responsibilities include application design, coding, testing, troubleshooting, architecture documentation, data analysis, system stability, and participation in agile engineering practices. The role uses .NET, C#, RESTful APIs, SQL, React or Angular, cloud technologies, and enterprise-authorized AI coding tools to deliver high-quality production systems.

Leads complex private-market valuation engagements for institutional clients, covering illiquid debt, equity, derivatives, and alternative investments. Applies DCF, comparable company, precedent transaction, option pricing, backsolve, waterfall, and scenario-based methodologies under ASC 820, IFRS 13, and IPEV guidelines. Oversees analyses, reviews models and reports, supports audit defense, manages client relationships, mentors junior professionals, and enhances valuation models, processes, and technology-enabled solutions.

Lead Build AI’s commercial function by personally closing complex, high-value deals with frontier AI labs and robotics companies. Define ideal customers, build pipeline, manage negotiations and contracts, structure pilots and multi-year partnerships, and collaborate with founders and technical teams. Establish a repeatable sales process, translate customer feedback into product direction, and eventually recruit and lead the sales organization.

Leverages AI to automate SOC operations, improve threat detection, conduct security assessments, and secure AI applications and services. Manages cloud security across AWS and Microsoft environments, including vulnerability remediation, IAM, WAF, DLP, and incident-response automation. Conducts threat hunting, evaluates AI governance and security controls, tracks vulnerabilities and threat intelligence, and supports secure AI-assisted development. Partners with security, applications, infrastructure, and university stakeholders on AI security, compliance, and risk management.

Build AI agents and workflows for insurance use cases, developing tailored end-to-end solutions that automate complex customer processes. Work across the full stack and modern AI technologies, balancing latency, cost, reliability, and safety. Collaborate with Product, GTM, Design, and Marketing teams while engaging directly with users in a fast-moving, ambiguous startup environment.

Develop, train, evaluate, optimize, and deploy machine learning models and AI applications using Python and PyTorch. Prepare datasets, build REST APIs for model serving, troubleshoot data and API issues, and maintain model versions and documentation. Collaborate with engineering, data science, and product teams while following software development practices such as Git, code reviews, automated testing, and deployment workflows.

Design, deploy, and maintain AI-powered applications and scalable cloud infrastructure. Responsibilities include managing AWS or Azure environments, implementing Terraform-based infrastructure, containerizing services with Docker, supporting AI/ML workload scaling, and establishing monitoring, logging, and alerting. The role also involves troubleshooting deployments, automating workflows, collaborating across engineering and data teams, documenting procedures, and following security and reliability best practices.

Design, develop, and deploy AI-powered applications using Python, LLMs, RAG pipelines, PyTorch, APIs, vector databases, and embedding models. Build AI agents, chatbots, and intelligent automation solutions; optimize model performance, scalability, latency, and accuracy; integrate AI systems with backend services; monitor deployments; and collaborate with engineering, data science, product, and cross-functional teams.

Develop and deploy AI-powered applications, integrating large language models, APIs, chatbots, RAG, embeddings, and vector databases. Build backend services, optimize application quality and performance, implement security and responsible AI practices, and monitor accuracy, latency, reliability, and costs. Collaborate with product, design, and engineering teams while supporting deployment and documentation.

Leads the digital employee experience strategy for more than 230,000 employees. Oversees employee-facing products, platforms, AI-enabled tools, automation, onboarding, self-service, and digital workplace initiatives from discovery through continuous improvement. Develops product roadmaps, establishes experience principles, partners with technology and HR teams, drives adoption, and measures outcomes through OKRs, KPIs, research, and analytics. Advises executives, advances responsible AI, eliminates employee friction, and leads enterprise-wide transformation and change.

Lead AI strategy and product development for investment research. Own the product lifecycle from strategy and roadmap through discovery, experimentation, software delivery, launch, adoption, and scaling. Partner with investment professionals, researchers, and technology teams to build AI-enabled research capabilities and data foundations using unstructured investment knowledge. Influence executives, align cross-functional priorities, measure business outcomes, and lead high-performing product teams.

Build AI-powered features and scalable agent infrastructure for Hex’s data analytics platform. Partner with research and product engineering teams on context, model prompting, experimentation tooling, and platform integration. Lead major product initiatives, develop performant web experiences, maintain high standards for testing and correctness, and mentor engineers. The role involves full-stack development across React, TypeScript, GraphQL, backend services, cloud infrastructure, and data systems.

Build and deploy AI capabilities for Hex’s Notebook Agent and context engine. Responsibilities include running experiments, fine-tuning models, developing AI infrastructure and experimentation tooling, architecting AI-enabled systems, and shipping production experiences for data scientists and analysts. The role partners closely with product teams, spans greenfield initiatives, and offers opportunities for technical and team leadership.

Build and deploy AI-powered automation workflows for marketing, growth, content, sales collateral, social distribution, and community operations. Responsibilities include auditing existing processes, automating blog production and publishing, encoding brand voice, integrating platform APIs, implementing human approval steps, documenting workflows, and handing them off to the team.

Leads enterprise business intelligence strategy, product roadmap, semantic modeling, reporting standards, and AI-assisted analytics initiatives. Partners with Data Engineering, Data Governance, Data Science, AI Solutions, and IT to deliver scalable, secure, governed BI capabilities. Oversees demand prioritization, adoption measurement, stakeholder engagement, and technical delivery while leading and developing the BI team.

Own complex healthcare AI deployments from initial brief through production. Design and build reliable multi-agent systems, establish evaluation and safety standards, integrate EHRs and legacy systems, and convert customer-proven solutions into scalable platform capabilities. Set architecture direction, manage timelines and outcomes, mentor engineers, document systems, and collaborate directly with healthcare customers and clinicians.

Own cross-account delivery planning for Applied AI deployments, including FDE capacity, dependencies, risks, and commitments. Establish Linear as the source of truth, improve estimation and delivery metrics, track progress, triage applied-versus-platform blockers, and convert recurring field needs into platform priorities. Run lightweight operating rhythms, automate status tracking, and ensure customer commitments reflect real capacity. The role requires technical credibility, strong engineering judgment, and relentless follow-through.

Own customer healthcare AI use cases from deployment brief through production. Build safe, evaluated multi-agent systems, integrate EHRs and legacy data, improve clinical workflows, and convert successful customer patterns into scalable platform capabilities. Mentor engineers, manage timelines, challenge unclear scope, and work directly with customers and clinicians.

Owns new-logo acquisition and full-cycle enterprise sales for Wood Mackenzie’s technology, AI, and digital infrastructure segment. Responsibilities include prospecting, territory planning, pipeline development, solution selling, negotiation, forecasting, CRM management, and contract execution. The role targets technology companies, cloud providers, AI infrastructure organizations, semiconductor manufacturers, and power technology providers. It also requires collaboration with Sales Development, Marketing, Research, Consulting, Product, and Account Management teams, plus customer engagement at industry events.